[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Galveia et al., 2018 - Google Patents

Computer aided diagnosis in ophthalmology: Deep learning applications

Galveia et al., 2018

Document ID
11264122900580639249
Author
Galveia J
Travassos A
Quadros F
da Silva Cruz L
Publication year
Publication venue
Classification in BioApps: Automation of Decision Making

External Links

Snippet

The automated diagnosis of ophthalmologic diseases to assist the medical ophthalmologist in their daily practice is the subject of much research. Recently, image processing based on very deep and complex processing structures became the focus of renewed interest, mostly …
Continue reading at link.springer.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00597Acquiring or recognising eyes, e.g. iris verification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05Recognition of patterns in medical or anatomical images
    • G06K2209/051Recognition of patterns in medical or anatomical images of internal organs
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image

Similar Documents

Publication Publication Date Title
Stolte et al. A survey on medical image analysis in diabetic retinopathy
Gegundez-Arias et al. A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model
Almotiri et al. Retinal vessels segmentation techniques and algorithms: a survey
Uysal et al. Computer-aided retinal vessel segmentation in retinal images: convolutional neural networks
Welikala et al. Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy
Singh et al. Deep learning system applicability for rapid glaucoma prediction from fundus images across various data sets
Dayana et al. An enhanced swarm optimization-based deep neural network for diabetic retinopathy classification in fundus images
Khandouzi et al. Retinal vessel segmentation, a review of classic and deep methods
de Moura et al. Joint diabetic macular edema segmentation and characterization in OCT images
Khanna et al. Deep learning based computer-aided automatic prediction and grading system for diabetic retinopathy
Qin et al. A review of retinal vessel segmentation for fundus image analysis
Mansour et al. Glaucoma detection using novel perceptron based convolutional multi-layer neural network classification
Fraz et al. Computational methods for exudates detection and macular edema estimation in retinal images: a survey
Kumar et al. Analysis of retinal blood vessel segmentation techniques: a systematic survey
Suchetha et al. Region of interest-based predictive algorithm for subretinal hemorrhage detection using faster R-CNN
Galveia et al. Computer aided diagnosis in ophthalmology: Deep learning applications
Guergueb et al. A review of deep learning techniques for glaucoma detection
Morales-Lopez et al. Cataract detection and classification systems using computational intelligence: A survey
Samant et al. A hybrid filtering-based retinal blood vessel segmentation algorithm
Pavani et al. Robust semantic segmentation of retinal fluids from SD-OCT images using FAM-U-Net
Langarizadeh et al. Decision support system for age-related macular degeneration using convolutional neural networks
Godishala et al. Survey on retinal vessel segmentation
Tavakoli Automated optic disk detection in fundus images using a combination of deep learning and local histogram matching
DEVI et al. IMPLEMENTING RESNET-50 TRANSFER LEARNING MODEL FOR DIAGNOSING OCT IMAGES FOR DETECTING AND CLASSIFYING DME ABNORMALITIES
Bhardwaj et al. A computational framework for diabetic retinopathy severity grading categorization using ophthalmic image processing